n this paper we present a system for preserving the privacy
of individuals in a video surveillance scenario. While a person’s privacy should not be revealed to a viewer of the video without special needs, it is still important that the action in a scene as the semantic content of a video remain perceivable by a human observer. The proposed system uses edge detection and adaptive thresholding in order to estimate the persons’ silhouettes in a video scene and thus rendering most of their actions visible, while hiding sensitive personal information. In order to obtain a more complete contour around a person, an adaptive thresholding scheme using edge histograms is used as well as background subtraction which limits the edge extraction to foreground masks and thus avoids distraction of the viewer’s eyes to background structures.